Dep-LLM is a training-free three-stage LLM framework that decomposes clinical interviews into clinical themes, modulates signals by token entropy, and outperforms zero-shot and supervised baselines on DAIC-WOZ and E-DAIC datasets.
Mental-llm: Leveraging large language models for mental health prediction via online text data,
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A review summarizing LLM applications for diagnostics and treatment in oncology, dermatology, dentistry, neurodegenerative disorders, and mental health, plus integration challenges.
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Dep-LLM: Training-Free Depression Diagnosis via Evidence-Guided Structured Multi-factor with Reliable LLM Reasoning
Dep-LLM is a training-free three-stage LLM framework that decomposes clinical interviews into clinical themes, modulates signals by token entropy, and outperforms zero-shot and supervised baselines on DAIC-WOZ and E-DAIC datasets.
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LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties
A review summarizing LLM applications for diagnostics and treatment in oncology, dermatology, dentistry, neurodegenerative disorders, and mental health, plus integration challenges.